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<H1>Shadow Removal via Shadow Image Decomposition</H1>
<DIV class="authors"><A href="https://lmhieu612.github.io/">Hieu 
Le</A>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;	  <A href="https://www3.cs.stonybrook.edu/~samaras/">Dimitris 
Samaras</A>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;	</DIV>
<DIV class="affiliations">
<P>Stony Brook University</P></DIV><!-- <div class="venue">Preprint Manuscript (<a href="https://arxiv.org/" target="_blank">Arxiv</a>) 2018</div> --> 
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<H2>Abstract</H2><BR>
<P>We propose a novel deep learning method for shadow removal. Inspired by 
physical models of shadow formation, we use a linear illumination transformation 
to model the shadow effects in the image that allows the shadow image to be 
expressed as a combination of the shadow-free image, the shadow parameters, and 
a matte layer. We use two deep networks, namely SP-Net and M-Net, to predict the 
shadow parameters and the shadow matte respectively. This system allows us to 
remove the shadow effects on the images. We train and test our framework on the 
most challenging shadow removal dataset (ISTD). Compared to the state-ofthe-art 
method, our model achieves a 40% error reduction in terms of root mean square 
error (RMSE) for the shadow area, reducing RMSE from 13.3 to 7.9. Moreover, we 
create an augmented ISTD dataset based on an image decomposition system by 
modifying the shadow parameters to generate new synthetic shadow images. 
Training our model on this new augmented ISTD dataset further lowers the RMSE on 
the shadow area to 7.4.	 </P></DIV>
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<H2>Examples</H2><BR>
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  <LI><A href="https://drive.google.com/open?id=1U_v-YjW4Eqlfac6MBNDPWSacR17r9Gtn" 
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  <LI><A href="http://vision.cs.stonybrook.edu/~hieule/SID//ISTD.zip" target="_blank">Results_ISTD_Trained_on_ISTD</A>
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  <LI><A href="http://vision.cs.stonybrook.edu/~hieule/SID//ISTD+.zip" target="_blank">Results_ISTD_Trained_on_ISTD+</A>
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  <LI><A href="https://drive.google.com/open?id=1aGS3fisgXASEqyVvMpwAJCHP__U-dknW" 
  target="_blank">Color Adjustment Code</A>	 </LI></UL></DIV>
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<H2>Citation</H2>
<DIV class="section bibtex">
<PRE>@InProceedings{Le_2019_ICCV,
	author = {Le, Hieu and Samaras, Dimitris},
	title = {Shadow Removal via Shadow Image Decomposition},
	booktitle = {The IEEE International Conference on Computer Vision (ICCV)},	
	month = {October},
	year = {2019}
}
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